StackResolve

Last 30 days

Uptime

100%

Response time

410 ms typical, 410 ms slowest 5%

Last check

1 h ago

Next check

in 4 h

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "stackresolve": {
      "type": "http",
      "url": "https://mcp.stackresolve.dev/mcp"
    }
  }
}

15 tools

• resolve

  Best tools for a natural-language task: resolves the task to the capabilities it needs, returns products that expose them ranked by fit and AgentReady score, each with a reason. Optional requirements (api/mcp/self_serve/openapi/cli) filter candidates. Set discover:true to search

• how_to

  BEFORE building something, call this: returns the CURRENT (date-stamped), cited, tool-aware way to do a task, so you build from today's best practice instead of training-cutoff memory. Composes live web research + the tool resolver + one synthesis pass into { approach, recommende

• find_tools_for_task

  Rank the software an agent should use for a task.

• search_tools

  Search the registry by query + requirements (api/mcp/self_serve/openapi/cli).

• compare_products

  Compare products by slug.

• get_profile

  Full registry profile (AgentReady Score, capabilities, sources).

• list_registry

  List the registry, highest AgentReady Score first.

• audit

  Audit a product for agent-readiness.

• generate_agent_interfaces

  Make a product agent-native: from its OpenAPI, generate an MCP server (one tool per operation), a CLI, an llms.txt, and Claude Code/Codex/Cursor install snippets.

• get_company

  Structured company record.

• get_pricing

  Normalized pricing.

• research_company

  Grounded, cited answer about a company.

• find_competitors

  Real competitors and alternatives for a company, extracted from live research and returned as structured rows.

• compare_companies

  Structured side-by-side of companies across fields (description, products, categories, funding, technology).

• get_usage

  Your usage this billing period (read-only).

Security scan

• No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

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